Abstract: Provided is a method for performing accurate object recognition in a stable manner in consideration of changes in a shooting environment. In such a method, a camera captures an image of a shooting location where an object is to be placed and an object included in an image of the shooting location is recognized utilizing a machine learning model for object recognition. The method further involves: determining necessity of an update operation on the machine learning model for object recognition at a predetermined time; when the update operation is necessary, causing the camera to capture an image of the shooting location where no object is placed to thereby re-acquire a background image for training; and causing the machine learning model to be trained using a composite image of a backgroundless object image and the re-acquired background image for training as training data.

Abstract: In collection of training data for image recognition, in order to support a reduction in collection of improper images which are not suitable as training data, a learning data collection device includes a processor which is configured to acquire a captured image from an image capturing device, determine whether or not the captured image is suitable as training data, and when the captured image is determined to be not suitable as training data, perform a notification operation to prompt an image capturing person to reshoot a new image for the captured image.

Abstract: Provided is a method for performing accurate object recognition in a stable manner in consideration of changes in a shooting environment. In such a method, a camera captures an image of a shooting location where an object is to be placed and an object included in an image of the shooting location is recognized utilizing a machine learning model for object recognition. The method further involves: determining necessity of an update operation on the machine learning model for object recognition at a predetermined time; when the update operation is necessary, causing the camera to capture an image of the shooting location where no object is placed to thereby re-acquire a background image for training; and causing the machine learning model to be trained using a composite image of a backgroundless object image and the re-acquired background image for training as training data.

Abstract: In generation of training data for image recognition, in order to reduce a user's workload of assigning a label to a captured image, a learning device includes a processor for performing operations to generate training data and a display device, wherein the processor is configured to acquire a captured image from an image capturing device; acquire one or more candidate objects recognized based on an identification model for a recognition target included in the captured image; and display, on the display device, information on the candidate objects as respective label candidates for the captured image.

Abstract: In collection of training data for image recognition, in order to support a reduction in collection of improper images which are not suitable as training data, a learning data collection device 3 includes a processor 51 which is configured to acquire a captured image from an image capturing device 2, determine whether or not the captured image is suitable as training data, and when the captured image is determined to be not suitable as training data, perform a notification operation to prompt an image capturing person to reshoot a new image for the captured image.

Abstract: In generation of training data for image recognition, in order to reduce a user's workload of assigning a label to a captured image, a learning device includes a processor for performing operations to generate training data and a display device, wherein the processor is configured to acquire a captured image from an image capturing device; acquire one or more candidate objects recognized based on an identification model for a recognition target included in the captured image; and display, on the display device, information on the candidate objects as respective label candidates for the captured image.